{
 "metadata": {
  "name": "",
  "signature": "sha256:52e6fe3832ad2ab4ade0e7484970ffa7b611a5f95f9a06b7c6f2cdf16ab56272"
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 "worksheets": [
  {
   "cells": [
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The field of [NILM](http://en.wikipedia.org/wiki/Nonintrusive_load_monitoring) has seen some exciting developments in the recent past. However, with the release of [nilmtk](http://nilmtk.github.io/), we are aiming to see how well different approaches line up. So, we were interested in bringing one of the [seminal work](http://georgehart.com/research/Hart1985.pdf) in NILM by [George Hart](http://georgehart.com/) to nilmtk and give it a spin. In this notebook, I'll present a very quick overview of the algorithm and test it out on a home from the [WikiEnergy](https://dataport.pecanstreet.org/) data set."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Customary imports"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "import numpy as np\n",
      "import pandas as pd\n",
      "from os.path import join\n",
      "\n",
      "from pylab import rcParams\n",
      "import matplotlib.pyplot as plt\n",
      "%matplotlib inline\n",
      "\n",
      "rcParams['figure.figsize'] = (12, 6)\n",
      "\n",
      "import nilmtk\n",
      "from nilmtk import DataSet, TimeFrame, MeterGroup, HDFDataStore\n",
      "from nilmtk.disaggregate import CombinatorialOptimisation\n",
      "from nilmtk.utils import print_dict\n",
      "from nilmtk.metrics import f1_score\n",
      "import seaborn as sns\n",
      "sns.set_palette(\"Set3\", n_colors=12)\n",
      "\n",
      "\n",
      "import warnings\n",
      "warnings.filterwarnings(\"ignore\")"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 1
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Version information"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from nilmtk.utils import dependencies_diagnostics\n",
      "pd.DataFrame(pd.Series(dependencies_diagnostics(), name=\"Value\"))"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>Value</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>Date</th>\n",
        "      <td>                        2014-11-28 20:28:14.025264</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>Platform</th>\n",
        "      <td> Linux-3.13.0-40-generic-x86_64-with-debian-jes...</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>System version</th>\n",
        "      <td>                                               2.7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>nilmtk version</th>\n",
        "      <td>                                         0.2.0.dev</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>nilm_metadata version</th>\n",
        "      <td>                                 0.2.0.dev-2a1e9f7</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>numpy version</th>\n",
        "      <td>                                             1.9.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>matplotlib version</th>\n",
        "      <td>                                             1.3.1</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>pandas version</th>\n",
        "      <td>                                            0.15.0</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>sklearn version</th>\n",
        "      <td>                                            0.14.1</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 2,
       "text": [
        "                                                                   Value\n",
        "Date                                          2014-11-28 20:28:14.025264\n",
        "Platform               Linux-3.13.0-40-generic-x86_64-with-debian-jes...\n",
        "System version                                                       2.7\n",
        "nilmtk version                                                 0.2.0.dev\n",
        "nilm_metadata version                                  0.2.0.dev-2a1e9f7\n",
        "numpy version                                                      1.9.0\n",
        "matplotlib version                                                 1.3.1\n",
        "pandas version                                                    0.15.0\n",
        "sklearn version                                                   0.14.1"
       ]
      }
     ],
     "prompt_number": 2
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Loading data"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "data_dir = '/home/nipun/Downloads/'\n",
      "we = DataSet(join(data_dir, 'wikienergy.h5'))\n",
      "print('loaded ' + str(len(we.buildings)) + ' buildings')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "loaded 239 buildings\n"
       ]
      }
     ],
     "prompt_number": 3
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Examine metadata for a single house"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "building_number = 11\n",
      "print_dict(we.buildings[building_number].metadata)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<ul><li><strong>instance</strong>: 11</li><li><strong>dataset</strong>: WikiEnergy</li><li><strong>original_name</strong>: 434</li></ul>"
       ],
       "metadata": {},
       "output_type": "display_data",
       "text": [
        "<IPython.core.display.HTML at 0x7f522de97850>"
       ]
      }
     ],
     "prompt_number": 4
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Let us perform our analysis on the first 2 days"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "we.store.window = TimeFrame(start='2014-04-01 00:00:00-05:00', end='2014-04-02 00:00:00-05:00')\n",
      "elec = we.buildings[building_number].elec\n",
      "elec.appliances"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 5,
       "text": [
        "[Appliance(type='fridge', instance=1),\n",
        " Appliance(type='dish washer', instance=1),\n",
        " Appliance(type='electric water heating appliance', instance=1),\n",
        " Appliance(type='spin dryer', instance=1),\n",
        " Appliance(type='electric furnace', instance=1),\n",
        " Appliance(type='sockets', instance=1),\n",
        " Appliance(type='sockets', instance=2),\n",
        " Appliance(type='air conditioner', instance=1),\n",
        " Appliance(type='sockets', instance=3),\n",
        " Appliance(type='sockets', instance=4)]"
       ]
      }
     ],
     "prompt_number": 5
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "mains = elec.mains()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 6
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Let us quickly have a look at what contribution different appliances have to the mains."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "elec.plot()\n",
      "plt.tight_layout()\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
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+QilVQSnVGGgOHNQ07SoQr5TytSw6fibTOUIIUWy2bNlE9+49c3wZX35Nm/Z6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\n0alUSqzDHrb/o7w/EVjL9q59HNd2b1E3VDAY6oZo4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       "text": [
        "<matplotlib.figure.Figure at 0x7f51f7a9cf90>"
       ]
      }
     ],
     "prompt_number": 7
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "From the plot above, a human could easily see the signature of 3 appliances: `Fridge`, `Air conditioner` and `Electric furnace`\n",
      "    \n",
      "We'll hope that our unsupervised implementation would be able to figure out these 3 appliances.    "
     ]
    },
    {
     "cell_type": "raw",
     "metadata": {},
     "source": [
      "Another way of understanding contribution of different appliances is via the following pie chart"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "fraction = elec.submeters().fraction_per_meter().dropna()\n",
      "labels = elec.get_appliance_labels(fraction.index)\n",
      "plt.figure(figsize=(8,8))\n",
      "fraction.plot(kind='pie', labels=labels);"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "\r",
        "1/10 ElecMeter(instance=2, building=11, dataset='WikiEnergy', appliances=[Appliance(type='air conditioner', instance=1)])"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Using cached result.\n",
        "Calculating energy for column ('power', 'active')\n"
       ]
      },
      {
       "ename": "ValueError",
       "evalue": "Indexes have overlapping values: <class 'pandas.tseries.index.DatetimeIndex'>\n[2014-04-01 05:00:00]\nLength: 1, Freq: None, Timezone: None",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-8-683776b415f6>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mfraction\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0melec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msubmeters\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfraction_per_meter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdropna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      2\u001b[0m \u001b[0mlabels\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0melec\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_appliance_labels\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfraction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mindex\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      3\u001b[0m \u001b[0mplt\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mfigure\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfigsize\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m8\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m8\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m      4\u001b[0m \u001b[0mfraction\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mplot\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mkind\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'pie'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlabels\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlabels\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m;\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/git/nilmtk/nilmtk/metergroup.pyc\u001b[0m in \u001b[0;36mfraction_per_meter\u001b[1;34m(self, **load_kwargs)\u001b[0m\n\u001b[0;32m    895\u001b[0m         \u001b[0mEach\u001b[0m \u001b[0mvalue\u001b[0m \u001b[1;32mis\u001b[0m \u001b[0ma\u001b[0m \u001b[0mfloat\u001b[0m \u001b[1;32min\u001b[0m \u001b[0mthe\u001b[0m \u001b[0mrange\u001b[0m \u001b[1;33m[\u001b[0m\u001b[1;36m0\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m.\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    896\u001b[0m         \"\"\"\n\u001b[1;32m--> 897\u001b[1;33m         \u001b[0menergy_per_meter\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0menergy_per_meter\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mload_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mmax\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    898\u001b[0m         \u001b[0mtotal_energy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0menergy_per_meter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msum\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    899\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0menergy_per_meter\u001b[0m \u001b[1;33m/\u001b[0m \u001b[0mtotal_energy\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/git/nilmtk/nilmtk/metergroup.pyc\u001b[0m in \u001b[0;36menergy_per_meter\u001b[1;34m(self, **load_kwargs)\u001b[0m\n\u001b[0;32m    885\u001b[0m             \u001b[1;32mprint\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'\\r{:d}/{:d} {}'\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mformat\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m+\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mn_meters\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmeter\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mend\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m''\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    886\u001b[0m             \u001b[0mstdout\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mflush\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 887\u001b[1;33m             \u001b[0mmeter_energy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmeter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtotal_energy\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m**\u001b[0m\u001b[0mload_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    888\u001b[0m             \u001b[0menergy_per_meter\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mmeter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0midentifier\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mmeter_energy\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    889\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0menergy_per_meter\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdropna\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mhow\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'all'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/git/nilmtk/nilmtk/elecmeter.pyc\u001b[0m in \u001b[0;36mtotal_energy\u001b[1;34m(self, **loader_kwargs)\u001b[0m\n\u001b[0;32m    446\u001b[0m         \u001b[0mnodes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mClip\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mTotalEnergy\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    447\u001b[0m         return self._get_stat_from_cache_or_compute(\n\u001b[1;32m--> 448\u001b[1;33m             nodes, TotalEnergy.results_class(), loader_kwargs)\n\u001b[0m\u001b[0;32m    449\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    450\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mdropout_rate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mloader_kwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/git/nilmtk/nilmtk/elecmeter.pyc\u001b[0m in \u001b[0;36m_get_stat_from_cache_or_compute\u001b[1;34m(self, nodes, results_obj, loader_kwargs)\u001b[0m\n\u001b[0;32m    545\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    546\u001b[0m             \u001b[1;31m# Merge cached results with newly computed\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 547\u001b[1;33m             \u001b[0mresults_obj\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mupdate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mcomputed_result\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mresults\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    548\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    549\u001b[0m             \u001b[1;31m# Save to disk newly computed stats\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/git/nilmtk/nilmtk/results.pyc\u001b[0m in \u001b[0;36mupdate\u001b[1;34m(self, new_result)\u001b[0m\n\u001b[0;32m    102\u001b[0m                             .format(self.__class__))\n\u001b[0;32m    103\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 104\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mappend\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mnew_result\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mverify_integrity\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    105\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_data\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0msort_index\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0minplace\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mTrue\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    106\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcheck_for_overlap\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/core/frame.pyc\u001b[0m in \u001b[0;36mappend\u001b[1;34m(self, other, ignore_index, verify_integrity)\u001b[0m\n\u001b[0;32m   3780\u001b[0m             \u001b[0mto_concat\u001b[0m \u001b[1;33m=\u001b[0m \u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mother\u001b[0m\u001b[1;33m]\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3781\u001b[0m         return concat(to_concat, ignore_index=ignore_index,\n\u001b[1;32m-> 3782\u001b[1;33m                       verify_integrity=verify_integrity)\n\u001b[0m\u001b[0;32m   3783\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m   3784\u001b[0m     def join(self, other, on=None, how='left', lsuffix='', rsuffix='',\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc\u001b[0m in \u001b[0;36mconcat\u001b[1;34m(objs, axis, join, join_axes, ignore_index, keys, levels, names, verify_integrity, copy)\u001b[0m\n\u001b[0;32m    720\u001b[0m                        \u001b[0mkeys\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mkeys\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mlevels\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mlevels\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mnames\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mnames\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    721\u001b[0m                        \u001b[0mverify_integrity\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mverify_integrity\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 722\u001b[1;33m                        copy=copy)\n\u001b[0m\u001b[0;32m    723\u001b[0m     \u001b[1;32mreturn\u001b[0m \u001b[0mop\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    724\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, objs, axis, join, join_axes, keys, levels, names, ignore_index, verify_integrity, copy)\u001b[0m\n\u001b[0;32m    852\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mcopy\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mcopy\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    853\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 854\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mnew_axes\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_new_axes\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    855\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    856\u001b[0m     \u001b[1;32mdef\u001b[0m \u001b[0mget_result\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc\u001b[0m in \u001b[0;36m_get_new_axes\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    917\u001b[0m                 \u001b[0mnew_axes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mi\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0max\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    918\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 919\u001b[1;33m         \u001b[0mnew_axes\u001b[0m\u001b[1;33m[\u001b[0m\u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0maxis\u001b[0m\u001b[1;33m]\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_get_concat_axis\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    920\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mnew_axes\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    921\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc\u001b[0m in \u001b[0;36m_get_concat_axis\u001b[1;34m(self)\u001b[0m\n\u001b[0;32m    974\u001b[0m                                                   self.levels, self.names)\n\u001b[0;32m    975\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 976\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_maybe_check_integrity\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mconcat_axis\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    977\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    978\u001b[0m         \u001b[1;32mreturn\u001b[0m \u001b[0mconcat_axis\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/tools/merge.pyc\u001b[0m in \u001b[0;36m_maybe_check_integrity\u001b[1;34m(self, concat_index)\u001b[0m\n\u001b[0;32m    983\u001b[0m                 \u001b[0moverlap\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mconcat_index\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mget_duplicates\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    984\u001b[0m                 raise ValueError('Indexes have overlapping values: %s'\n\u001b[1;32m--> 985\u001b[1;33m                                 % str(overlap))\n\u001b[0m\u001b[0;32m    986\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    987\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mValueError\u001b[0m: Indexes have overlapping values: <class 'pandas.tseries.index.DatetimeIndex'>\n[2014-04-01 05:00:00]\nLength: 1, Freq: None, Timezone: None"
       ]
      }
     ],
     "prompt_number": 8
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The air conditioner, fridge and electric furnace together consume around 80% of total energy."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Training"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We'll now do the training from the aggregate data. The algorithm segments the time series data into steady and transient states. Thus, we'll first figure out the transient and the steady states. Next, we'll try and pair the on and the off transitions based on their proximity in time and value. "
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "from nilmtk.disaggregate.hart_85 import Hart85\n",
      "h = Hart85()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 9
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.train(mains)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Finding Edges, please wait ...\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Edge detection complete.\n",
        "Creating transition frame ...\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "Transition frame created.\n",
        "Creating states frame ...\n"
       ]
      },
      {
       "output_type": "stream",
       "stream": "stdout",
       "text": [
        "States frame created.\n",
        "Finished.\n"
       ]
      }
     ],
     "prompt_number": 10
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "We obtain the set of steady states as follows (only top 10 entries shown for ease of view)"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.steady_states.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>active average</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:00:00-05:00</th>\n",
        "      <td> 755.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:06:00-05:00</th>\n",
        "      <td> 607.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:09:00-05:00</th>\n",
        "      <td> 505.250000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:25:00-05:00</th>\n",
        "      <td> 358.666667</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:31:00-05:00</th>\n",
        "      <td> 502.090909</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 11,
       "text": [
        "                           active average\n",
        "2014-04-01 00:00:00-05:00      755.500000\n",
        "2014-04-01 00:06:00-05:00      607.500000\n",
        "2014-04-01 00:09:00-05:00      505.250000\n",
        "2014-04-01 00:25:00-05:00      358.666667\n",
        "2014-04-01 00:31:00-05:00      502.090909"
       ]
      }
     ],
     "prompt_number": 11
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The table above shows the steady power states observed in the mains data. Another way of understanding the same is by looking at the start of steady states overlayed on top of mains power consumption, shown as follows."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "sns.set_palette(\"Set1\", n_colors=12)\n",
      "ax = mains.plot()\n",
      "h.steady_states['active average'].plot(style='o', ax = ax);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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fjBfe/Wew+p8H0mmv7Oa1K7FuxxPozwlR74YRqCOLPDauWV2vXteNsCiAY86/nwD4Duzt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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f51f6e15110>"
       ]
      }
     ],
     "prompt_number": 12
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The difference b/w successive steady states gives us the transitions b/w them. The following table shows the obtained transitions (again only top 10 entries shown)."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.transients.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>active transition</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:00:00-05:00</th>\n",
        "      <td> 755.500000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:06:00-05:00</th>\n",
        "      <td>-148.000000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:09:00-05:00</th>\n",
        "      <td>-102.250000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:25:00-05:00</th>\n",
        "      <td>-146.583333</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2014-04-01 00:31:00-05:00</th>\n",
        "      <td> 143.424242</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 13,
       "text": [
        "                           active transition\n",
        "2014-04-01 00:00:00-05:00         755.500000\n",
        "2014-04-01 00:06:00-05:00        -148.000000\n",
        "2014-04-01 00:09:00-05:00        -102.250000\n",
        "2014-04-01 00:25:00-05:00        -146.583333\n",
        "2014-04-01 00:31:00-05:00         143.424242"
       ]
      }
     ],
     "prompt_number": 13
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "These transitions when seen on the time series would appear as follows:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.transients['active transition'].plot(style='o')\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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EOlM79v+Wk3ZdJ12xvCGtEq1UKbFo97pXohaBCJSakjLtvnuiHnAjItnX7FaJ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\niopeBvwWwN23Ap8APhPuj7a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OzhL3e0haJ0eBV8Z6ASiRdqWuARFphq4x/1cUWgx+ACwp\nlJnZwWY20IS6iUgRtQiISCPky9wfO16g1LYF7wAuCt0HAE8DZwFbGlJDERERERERERERERERERER\nERERERERERERERERERERERGRyP1/42cqRJ+4Wh4AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f51f6b3b750>"
       ]
      }
     ],
     "prompt_number": 14
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Next, we pair the on (positive) and the off (negative) transitions as shown in the table below."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.pair_df.head()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>T1 Time</th>\n",
        "      <th>T1 Active</th>\n",
        "      <th>T2 Time</th>\n",
        "      <th>T2 Active</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>2014-04-01 05:31:00</td>\n",
        "      <td> 143.424242</td>\n",
        "      <td>2014-04-01 05:43:00</td>\n",
        "      <td>-145.690909</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td>2014-04-01 05:49:00</td>\n",
        "      <td> 144.145455</td>\n",
        "      <td>2014-04-01 06:01:00</td>\n",
        "      <td>-138.212121</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>2014-04-01 06:08:00</td>\n",
        "      <td> 141.484848</td>\n",
        "      <td>2014-04-01 06:19:00</td>\n",
        "      <td>-145.984848</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>3</th>\n",
        "      <td>2014-04-01 06:26:00</td>\n",
        "      <td> 144.766667</td>\n",
        "      <td>2014-04-01 06:37:00</td>\n",
        "      <td>-145.600000</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>4</th>\n",
        "      <td>2014-04-01 06:44:00</td>\n",
        "      <td> 145.600000</td>\n",
        "      <td>2014-04-01 06:55:00</td>\n",
        "      <td>-143.100000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 15,
       "text": [
        "              T1 Time   T1 Active             T2 Time   T2 Active\n",
        "0 2014-04-01 05:31:00  143.424242 2014-04-01 05:43:00 -145.690909\n",
        "1 2014-04-01 05:49:00  144.145455 2014-04-01 06:01:00 -138.212121\n",
        "2 2014-04-01 06:08:00  141.484848 2014-04-01 06:19:00 -145.984848\n",
        "3 2014-04-01 06:26:00  144.766667 2014-04-01 06:37:00 -145.600000\n",
        "4 2014-04-01 06:44:00  145.600000 2014-04-01 06:55:00 -143.100000"
       ]
      }
     ],
     "prompt_number": 15
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "The following image borrowed from Hart's paper summarises the above discussion."
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "![](http://i.imgur.com/vU2ZgD4.png)"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Once, we obtain these pairings, we consider a particular appliance usage as the average of the magnitude of the on and the off transition. Then, we use a non-parametric clustering method to obtain the number of appliances and the corresponding power draws. This step in our implementation is different from what was originally proposed by George Hart. Once done, we obtain the learnt appliances as follows:"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.centroids"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "html": [
        "<div style=\"max-height:1000px;max-width:1500px;overflow:auto;\">\n",
        "<table border=\"1\" class=\"dataframe\">\n",
        "  <thead>\n",
        "    <tr style=\"text-align: right;\">\n",
        "      <th></th>\n",
        "      <th>active</th>\n",
        "    </tr>\n",
        "  </thead>\n",
        "  <tbody>\n",
        "    <tr>\n",
        "      <th>0</th>\n",
        "      <td>  146.458708</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>1</th>\n",
        "      <td> 3532.218934</td>\n",
        "    </tr>\n",
        "    <tr>\n",
        "      <th>2</th>\n",
        "      <td>  911.500000</td>\n",
        "    </tr>\n",
        "  </tbody>\n",
        "</table>\n",
        "</div>"
       ],
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 16,
       "text": [
        "        active\n",
        "0   146.458708\n",
        "1  3532.218934\n",
        "2   911.500000"
       ]
      }
     ],
     "prompt_number": 16
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So, we obtain 3 appliances as per our unsupervised learning algorithm. Based on the power draw, I think I see air conditioner and refrigerator there. What is the third one? Not sure."
     ]
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Disaggregation"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Disaggregation follows much of the same method as training. During disaggregation, we also assign transients from the learnt model."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a = elec.power_series(load_all_power_columns=True).next()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 17
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a.index[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 18,
       "text": [
        "Timestamp('2014-04-01 00:00:00-0500', tz='US/Central')"
       ]
      }
     ],
     "prompt_number": 18
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.transients.index[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 19,
       "text": [
        "Timestamp('2014-04-01 00:00:00-0500', tz='US/Central')"
       ]
      }
     ],
     "prompt_number": 19
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disag_filename = join(data_dir, 'wikienergy-disag.h5')\n",
      "output = HDFDataStore(disag_filename, 'w')\n",
      "h.disaggregate(mains, output)"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "ValueError",
       "evalue": "The file '/home/nipun/Downloads/wikienergy-disag.h5' is already opened.  Please close it before reopening in write mode.",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mValueError\u001b[0m                                Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-21-9275180041eb>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[0;32m      1\u001b[0m \u001b[0mdisag_filename\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mjoin\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdata_dir\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'wikienergy-disag.h5'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m----> 2\u001b[1;33m \u001b[0moutput\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mHDFDataStore\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdisag_filename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'w'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m      3\u001b[0m \u001b[0mh\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdisaggregate\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmains\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0moutput\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/git/nilmtk/nilmtk/datastore.pyc\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, filename, mode)\u001b[0m\n\u001b[0;32m     67\u001b[0m             \u001b[0mFile\u001b[0m \u001b[0mopen\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m.\u001b[0m  \u001b[0me\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mg\u001b[0m\u001b[1;33m.\u001b[0m \u001b[1;34m'a'\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;34m'r'\u001b[0m \u001b[1;32mor\u001b[0m \u001b[1;34m'w'\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     68\u001b[0m         \"\"\"\n\u001b[1;32m---> 69\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mstore\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mpd\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mHDFStore\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mfilename\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcomplevel\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;36m9\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mcomplib\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;34m'blosc'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m     70\u001b[0m         \u001b[0msuper\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mHDFDataStore\u001b[0m\u001b[1;33m,\u001b[0m \u001b[0mself\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m__init__\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m     71\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/io/pytables.pyc\u001b[0m in \u001b[0;36m__init__\u001b[1;34m(self, path, mode, complevel, complib, fletcher32, **kwargs)\u001b[0m\n\u001b[0;32m    421\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_fletcher32\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mfletcher32\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    422\u001b[0m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0m_filters\u001b[0m \u001b[1;33m=\u001b[0m \u001b[0mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 423\u001b[1;33m         \u001b[0mself\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mopen\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mmode\u001b[0m\u001b[1;33m,\u001b[0m \u001b[1;33m**\u001b[0m\u001b[0mkwargs\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    424\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    425\u001b[0m     \u001b[1;33m@\u001b[0m\u001b[0mproperty\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;32m/home/nipun/anaconda/lib/python2.7/site-packages/pandas/io/pytables.pyc\u001b[0m in \u001b[0;36mopen\u001b[1;34m(self, mode, **kwargs)\u001b[0m\n\u001b[0;32m    572\u001b[0m                                                                                     hdf_version=tables.get_hdf5_version()))\n\u001b[0;32m    573\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[1;32m--> 574\u001b[1;33m             \u001b[1;32mraise\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m\u001b[0;32m    575\u001b[0m \u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0;32m    576\u001b[0m         \u001b[1;32mexcept\u001b[0m \u001b[1;33m(\u001b[0m\u001b[0mException\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;32mas\u001b[0m \u001b[0me\u001b[0m\u001b[1;33m:\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
        "\u001b[1;31mValueError\u001b[0m: The file '/home/nipun/Downloads/wikienergy-disag.h5' is already opened.  Please close it before reopening in write mode."
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.schunk[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 22,
       "text": [
        "localminute\n",
        "2014-04-01 00:00:00-05:00   -1\n",
        "2014-04-01 00:01:00-05:00   -1\n",
        "2014-04-01 00:02:00-05:00   -1\n",
        "2014-04-01 00:03:00-05:00   -1\n",
        "2014-04-01 00:04:00-05:00   -1\n",
        "2014-04-01 00:05:00-05:00   -1\n",
        "2014-04-01 00:06:00-05:00    0\n",
        "2014-04-01 00:07:00-05:00   -1\n",
        "2014-04-01 00:08:00-05:00   -1\n",
        "2014-04-01 00:09:00-05:00    0\n",
        "2014-04-01 00:10:00-05:00   -1\n",
        "2014-04-01 00:11:00-05:00   -1\n",
        "2014-04-01 00:12:00-05:00   -1\n",
        "2014-04-01 00:13:00-05:00   -1\n",
        "2014-04-01 00:14:00-05:00   -1\n",
        "...\n",
        "2014-04-01 23:45:00-05:00   -1\n",
        "2014-04-01 23:46:00-05:00   -1\n",
        "2014-04-01 23:47:00-05:00   -1\n",
        "2014-04-01 23:48:00-05:00   -1\n",
        "2014-04-01 23:49:00-05:00   -1\n",
        "2014-04-01 23:50:00-05:00   -1\n",
        "2014-04-01 23:51:00-05:00   -1\n",
        "2014-04-01 23:52:00-05:00   -1\n",
        "2014-04-01 23:53:00-05:00   -1\n",
        "2014-04-01 23:54:00-05:00   -1\n",
        "2014-04-01 23:55:00-05:00   -1\n",
        "2014-04-01 23:56:00-05:00   -1\n",
        "2014-04-01 23:57:00-05:00   -1\n",
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     "prompt_number": 22
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    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "plt.plot(h.po[2])"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 23,
       "text": [
        "[<matplotlib.lines.Line2D at 0x7f51f6ac2dd0>]"
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      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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       "text": [
        "<matplotlib.figure.Figure at 0x7f522e6cf0d0>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "a.index.values[0]"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 24,
       "text": [
        "numpy.datetime64('2014-04-01T01:00:00.000000000-0400')"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "cc/np.timedelta64(1,'ns')"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "ename": "NameError",
       "evalue": "name 'cc' is not defined",
       "output_type": "pyerr",
       "traceback": [
        "\u001b[1;31m---------------------------------------------------------------------------\u001b[0m\n\u001b[1;31mNameError\u001b[0m                                 Traceback (most recent call last)",
        "\u001b[1;32m<ipython-input-25-47fb4f3d98bf>\u001b[0m in \u001b[0;36m<module>\u001b[1;34m()\u001b[0m\n\u001b[1;32m----> 1\u001b[1;33m \u001b[0mcc\u001b[0m\u001b[1;33m/\u001b[0m\u001b[0mnp\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mtimedelta64\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;36m1\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;34m'ns'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n\u001b[0m",
        "\u001b[1;31mNameError\u001b[0m: name 'cc' is not defined"
       ]
      }
     ],
     "prompt_number": 25
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "h.transients.index.tz"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "pyout",
       "prompt_number": 26,
       "text": [
        "<DstTzInfo 'US/Central' LMT-1 day, 18:09:00 STD>"
       ]
      }
     ],
     "prompt_number": 26
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "output.close()"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 27
    },
    {
     "cell_type": "heading",
     "level": 3,
     "metadata": {},
     "source": [
      "Comparison with ground truth"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Since we used an unsupervised approach, we don't have labels (as of yet) for the learnt appliances. Thus, we can't directly use accuracy metrics directly (as of yet, maybe in a newer version we can). I'll compare the power draw using our disaggregation with ground truth manually."
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "disag = DataSet(disag_filename)\n",
      "disag_elec = disag.buildings[building_number].elec"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [],
     "prompt_number": 28
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Comparing for Fridge"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 0].plot()\n",
      "ax2 = elec['fridge', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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cSPsbgQ9N0zRw3i53I4BhGPsBFwD7AacBjxiGscNvcZsrWl4QBEEQ2kNbBWbK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WRoCFi4zdVKZvlPN/zsaTcKMRYekxJ2119//kR9a83ycHn1KpwSvF5borlPtd4a6a9TpxIo0sZK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\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f51f6e25590>"
       ]
      }
     ],
     "prompt_number": 29
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 0].plot()\n",
      "ax2 = elec['fridge', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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2drOCKBVEnKLAOgZZNM6x1gIxIiIS7SzLqtdjren2xGkKrGNQ6CXNtUCMiIhEt0ZLmru0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nQ40JCxvae+DS1a7bcU3mFgIFmTj8jAbbTFP7xAhtqngFJCna3k8CK0DMC61125XOAPHwlzEctN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\nOjr2i/8foMrzwQ+EO0EAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fafaf06c110>"
       ]
      }
     ],
     "prompt_number": 21
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Comparing for air conditioner"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 1].plot()\n",
      "ax2 = elec['air conditioner', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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OuC2QR4Gi5YhbQGu9RSn1v8ARwDql1Eqt9VpXRf+UG201sEco2e44M/rV7nU4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\nw0Ava7mnaNlerlVn9v7gNt9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zrwHPxbHAfwlwDLAJuBU4r3KJgiA8jYhb45tmXXkdmJ1I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\nn71HcQM9Q34p0U3W+M19LWZNVeVT7zKWeqpQRI3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odo7FScVThxeftQcW0TkGfS0kWDFI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\nwzAMwzAMA/j/mj2cyEPFlfwAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f51ce398590>"
       ]
      }
     ],
     "prompt_number": 30
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 1].plot()\n",
      "ax2 = elec['air conditioner', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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7A/CDdZ08fNRbAdgyNsUVdzzTNkU7yyP5Vfsv4th9BrjzyU3c/sTGTDIrtSrH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\nrvvQNZFXYfbXPl6wJpvCHrhoJwyc6fym/TcjYQb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ev7pc1PosGppYiCK026yxGZqXhHZ9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eszxr0a2vbFyfOlXjrWdV8/WbQvxV13nUFyYN5Kk0U6SaLVuVPSkWsAvF0p9T4A/wjgz/NwfT8L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\nhBBCCCGEEEIIIYSQvcr/D8d08XJaqoc7AAAAAElFTkSuQmCC\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fafaef089d0>"
       ]
      }
     ],
     "prompt_number": 22
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "While the timing looks impeccable, there seems to be some ambiguity in the power measurement :("
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Comparing for the `unknown` appliance"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 2].plot()\n",
      "ax2 = elec['electric furnace', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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teyzuxrLY569qo8lx4vNPymvGHP9mUa8n91psgJXcS3Jv6Z3E2RPNO/ceg+i5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\njuM4juM4juM4juM4juM4juM4juMUPP8PU59BowNJwJYAAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7f51f6af9690>"
       ]
      }
     ],
     "prompt_number": 31
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 2].plot()\n",
      "ax2 = elec['electric furnace', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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dDGAYwAzf9zsAzACwEsD7AFwZHXMlgPdHv58E4Fql1LBSaimAJQCOG9cWE0IIIYQQGabw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\nZ0uOViR7EFQuoiiKogyNd+c34hxIX92oHNcVz9paucCA9XPqDgen7xy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Fwg5ipt17+1AK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\nURRFUZSVyP8HfhY2DFG4i98AAAAASUVORK5CYII=\n",
       "text": [
        "<matplotlib.figure.Figure at 0x7fafaec9b950>"
       ]
      }
     ],
     "prompt_number": 23
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "So, this doesn't look to be a good fit. Maybe, the dish washer?"
     ]
    },
    {
     "cell_type": "code",
     "collapsed": false,
     "input": [
      "ax1 = disag_elec['unknown', 2].plot()\n",
      "ax2 = elec['dish washer', 1].plot()\n",
      "ax1.legend([\"Predicted\", \"Ground truth\"]);\n",
      "plt.ylabel(\"Power (W)\")\n",
      "plt.xlabel(\"Time\");"
     ],
     "language": "python",
     "metadata": {},
     "outputs": [
      {
       "metadata": {},
       "output_type": "display_data",
       "png": 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2K1+JiIiIVCllsif3NERaV7tPdjOFHLUmo8Gj8evCS7JRNmU3yM7n8ykiIiJS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\nI8zsxMj6p4CjzOyW6NdLYVbxIGA3M7uo5gPkTGQ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       "text": [
        "<matplotlib.figure.Figure at 0x7fafae422450>"
       ]
      }
     ],
     "prompt_number": 24
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Probably, a decent fit. Not really sure though!"
     ]
    },
    {
     "cell_type": "markdown",
     "metadata": {},
     "source": [
      "Broadly speaking, this 30 year algorithm seems to be doing a fairly decent job. The fact that this is unsupervised makes it all the more useful. There is some more work to be done on this algorithm. So, watch out for more posts and updates. Looking forward to your comments and feedback."
     ]
    }
   ],
   "metadata": {}
  }
 ]
}